AI Engineer

• Design and develop AI‑enabled software solutions that accelerate productivity across Emerson’s Test & Measurement business unit
• Rapidly prototype and iterate on ideas, using AI to quickly learn new technologies and deliver working solutions
• Integrate applications with enterprise systems (Microsoft ecosystem, Snowflake, Salesforce, Oracle)
• Collaborate closely with product owners, analysts, and business partners to validate needs and deliver solutions
• Build reusable patterns and guide others in effective use of AI tools to strengthen developer enablement
• Navigate ambiguity confidently and adapt to shifting priorities while upholding high standards for software quality, security, and reliability

Senior AI Software Engineer

• Contribute to the development of scalable algorithms for processing large datasets, implement and evaluate machine learning and deep learning algorithms for Natural Language Processing/Understanding.
• Assist in the design, development, and testing of ML models and pipelines for real-time processing of unstructured data.
• Collaborate with senior team members to analyze the impact of algorithm changes.
• Learn and grow under mentorship, gaining exposure to industry-standard NLP tools and techniques.

• Design and develop AI-powered enterprise applications on SAP Business Technology Platform (BTP).
• Build scalable backend services using the SAP Cloud Application Programming Model (CAP).
• Develop modern user interfaces with SAPUI5/Fiori and/or Angular.
• Integrate SAP AI Core and AI Foundation services into business applications.
• Design and implement integrations using REST APIs and SAP HANA Cloud.
• Develop and maintain data pipelines supporting AI use cases, including Retrieval-Augmented Generation (RAG) architectures.
• Containerize applications and AI services using Docker and deploy them within SAP BTP environments.
• Leverage AI-powered development tools such as GitHub Copilot and Cursor to improve development efficiency.
• Participate in code reviews, agile ceremonies, and technical knowledge sharing.
• Continuously evaluate and introduce emerging AI technologies and development best practices.

SAP ABAP AI Developer

• Lead implementation of AI, GenAI, ML, automation, and AI-powered applications
• Translate solution designs and requirements into development plans and working software
• Drive engineering delivery aligned with the target architecture
• Guide development teams on coding, integrations, testing, and operational readiness
• Build GenAI and agentic solutions using RAG, embeddings, vector search, prompt engineering, tool calling, and workflow orchestration
• Implement AI safety, quality controls, testing, and evaluation frameworks
• Design and develop APIs, backend services, integrations, cloud-native components, and supporting front-end functionality
• Lead code quality, reviews, CI/CD, documentation, and engineering best practices
• Support deployments, monitoring, troubleshooting, performance optimization, and operational handover
• Develop secure integrations with enterprise systems, data platforms, and business applications
• Build cloud-native AI solutions, preferably on Azure AI services and platform components
• Use AI-assisted development tools responsibly, ensuring human validation of outputs
• Mentor engineers, coordinate technical delivery, and communicate progress, risks, and decisions to stakeholders.

Lead AI Engineer

Machine Learning Engineer

• Guide architectural decisions for mixed (VLM, LLM, DNN) computer vision and multimodal systems.
• Drive the implementation of novel ML approaches, engineering best practices, and new technologies.
• Lead technical design reviews and architecture discussions.
• Establish standards and patterns for model development, evaluation, deployment, and production readiness.
• Architect scalable, reliable, and high-performance ML solutions.
• Lead the development of complex ML systems and architectures in the field of Intelligent Document Processing (IDP).
• Drive optimization of model performance, efficiency, and scalability.
• Improve ML development, validation, deployment, and operational processes.
• Ensure production readiness, system reliability, and technical excellence across ML initiatives.
• Mentor and develop senior and junior machine learning engineers.
• Foster a culture of engineering excellence, knowledge sharing, and continuous learning.
• Guide technical decision-making and provide feedback through design reviews.
• Support the career growth of team members while maintaining high engineering standards.

Senior Machine Learning Engineer

Computer Vision Engineer

• Designing, developing, and improving ball and player tracking algorithms using multi-camera systems
• Owning and evolving multi-view geometry solutions for accurate, court-wide tracking
• Developing robust approaches to occlusion handling, recovery, and failure modes in fast-paced sports scenarios
• Enhancing and maintaining mature, long-running computer vision systems used in live production
• Optimising algorithms for performance and reliability, including CPU and GPU considerations
• Contributing to cross-platform systems, ensuring algorithms run consistently across environments
• Supporting the integration of algorithms into cloud-enabled and distributed systems
• Working in an agile environment to deliver robust, production-ready solutions at scale
• Lead the development and improvement of computer vision algorithms from concept through to production
• Design, implement, test, and validate complex algorithmic features
• Take ownership of algorithmic components and drive their long-term maintainability and technical quality
• Collaborate closely with engineers across computer vision, tracking, tooling, and platform teams
• Contribute to technical discussions around architecture, performance, scalability, and deployment
• Identify weaknesses in existing approaches and propose pragmatic improvements
• Share progress, decisions, and learnings with the wider team
• Support and mentor other engineers through code reviews and technical guidance

Senior Computer Vision Engineer

• Build and improve deepfake and liveness detection models using CNNs, attention layers and vision-language models.
• Design, train and evaluate models end to end, from preparing data to checking results, following good engineering practices.
• Fine-tune vision-language models using efficient methods such as LoRA.
• Make models smaller and faster for both cloud and on-device / mobile use.
• Build and maintain training and deployment pipelines to get models into production on AWS (e.g. EC2, Athena).
• Use AI-assisted coding tools such as Claude Code to speed up experimentation and prototyping.
• Share progress clearly with technical and non-technical colleagues, and own independent research & development initiatives.

• Designing and developing new machine learning models with a focus on real-time performance.
• Integrating cutting-edge ML features into our SkeleTRACK product.
• Analysing model performance and identifying areas of improvement.
• Mentoring junior engineers and driving technical discussions.
• Collaborating with annotation teams to ensure data quality and workflow efficiency.
• Staying ahead of the curve by keeping up with CV/ML research and attending top conferences.
• Proactively identifying problems and owning solutions from design to delivery.

Machine Learning Engineer jobs in Hungary

See all jobs on JobTailor

Senior AI Software Engineer

AI Engineer

SAP ABAP AI Developer

Lead AI Engineer

Senior Machine Learning Engineer

Senior Computer Vision Engineer

Senior Computer Vision Engineer

Senior Machine Learning Engineer